A Complex Systems Approach to NEV Disruptive Innovation Diffusion: Co-Evolution Across Enterprise and Consumer Networks

Consumer attitude uncertainty can hinder disruptive innovation (DI) diffusion in the new energy vehicle (NEV) market and weaken enterprises’ incentives to adopt new technologies. This study develops a dual-layer coupled network model linking consumer attitude dissemination and enterprise R&D strategy evolution under bounded observability. Our simulations show three main findings. First, stronger discouragement of counter-attitudinal dissemination markedly suppresses diffusion and lowers steady-state adoption. Second, diffusion strengthens when consumers weight public information more and firm messaging less, particularly under stronger policy support. Third, network structure shapes diffusion: stronger inter-enterprise connectivity increases adoption, and consumer topology and interaction breadth exert different effects under different network types. These results clarify how information environments, policy support, and cross-layer behavioral modulation jointly shape diffusion regimes.

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Publication Details

Journal
Systems
Published
2026-02-04
DOI
https://doi.org/10.3390/systems14020172
Primary Topic
Innovation Diffusion and Forecasting
Type
article
Field-Weighted Citation Impact
0.00

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article

A Complex Systems Approach to NEV Disruptive Innovation Diffusion: Co-Evolution Across Enterprise and Consumer Networks

Kang Du, Ruguo Fan, Dingyi Liu, Liu Yang
Systems
Innovation Diffusion and Forecasting
article

A Complex Systems Approach to NEV Disruptive Innovation Diffusion: Co-Evolution Across Enterprise and Consumer Networks

Kang Du, Ruguo Fan, Dingyi Liu, Liu Yang
article en

Abstract

Consumer attitude uncertainty can hinder disruptive innovation (DI) diffusion in the new energy vehicle (NEV) market and weaken enterprises’ incentives to adopt new technologies. This study develops a dual-layer coupled network model linking consumer attitude dissemination and enterprise R&D strategy evolution under bounded observability. Our simulations show three main findings. First, stronger discouragement of counter-attitudinal dissemination markedly suppresses diffusion and lowers steady-state adoption. Second, diffusion strengthens when consumers weight public information more and firm messaging less, particularly under stronger policy support. Third, network structure shapes diffusion: stronger inter-enterprise connectivity increases adoption, and consumer topology and interaction breadth exert different effects under different network types. These results clarify how information environments, policy support, and cross-layer behavioral modulation jointly shape diffusion regimes.

SystemsVol. 14(2)
Wuhan University (CN), Nanjing University of Posts and Telecommunications (CN)
National Office for Philosophy and Social Sciences
Industry, innovation and infrastructure
Openalex Percentile: Top 70%
Innovation Diffusion and Forecasting
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